Methods and kits for predicting a response to an erythropoietic agent

ABSTRACT

Methods for predicting a response to an erythropoietic agent in a subject include providing a biological sample from the subject, and determining an amount in the sample of at least one peptide selected from the group consisting of SEQ ID NOS: 1-17. If there is a measurable difference in the amount of the at least one peptide in the sample, when compared to a control level of the same peptide, the subject is then predicted to have a good response or a poor response to the erythropoietic agent.

RELATED APPLICATIONS

This application is a continuation application of U.S. application Ser.No. 13/167,478, filed Jun. 23, 2011, and which claims priority from U.S.Provisional Application Ser. No. 61/357,843, filed Jun. 23, 2010, theentire disclosures of which are incorporated herein by this reference.

GOVERNMENT INTEREST

This invention was made with U.S. Government support under Grant NumbersP30ES014443, DK085673-01, DK077331, and DK072085 awarded by the NationalInstitutes of Health; Grant Number DE-FG02-05ER6406 awarded by the U.S.Department of Energy; and individual Merit Awards awarded by theDepartment of Veterans Affairs to Drs. Michael E. Brier and Jon B.Klein. The government has certain rights in this invention.

TECHNICAL FIELD

The presently-disclosed subject matter relates to methods and kits forpredicting a response to an erythropoietic agent in a subject. Inparticular, the presently-disclosed subject matter relates to methodsand kits for predicting a response to an erythropoietic agent that arebased on determining an amount of one or more peptide biomarkers in abiological sample from a subject.

BACKGROUND

The production of red blood cells, or erythropoiesis, is regulated bythe sensing of the oxygen carrying capacity of the blood by the kidneyand the subsequent production and release of erythropoietin (EPO). Innormal individuals, that production and release of EPO allows hemoglobin(Hb) concentrations to be maintained at normal levels. In many patientpopulations, however, the administration of exogenous EPO is required tomaintain Hb concentrations above 10 g/dL. These patient populations arediverse and include patients with chronic renal disease, HIV-infection,and cancer.

EPO is a glycoprotein hormone that exerts its erythropoietic effectthrough the EPO receptor (EpoR) and, as such, there is a series of bothextra and intracellular events that must occur for EPO to regulate redblood cell production. Along these lines, and central to the currentdiscussion of erythropoietic agents such as EPO, it has been observedthat certain patients respond normally to pharmacologic concentrationsof EPO (good responders), while other patients do not respond to typicalpharmacologic concentrations (poor responders). Patients that are poorresponders to EPO may be at risk for increased morbidity and mortality(1). Indeed, it has been further observed that the inability of thesepatients to reach a target hemoglobin concentration, in combination withthe increased epoetin-α dose that must typically be administered, placesthese patients at an increased risk of death, myocardial infarction,congestive heart failure, or stroke (2).

Many factors may cause a poor response to an erythropoietic agent, suchas EPO, including inadequate doses of the agent, functional or absoluteiron deficiency, blood loss, infection, inflammation, secondaryhyperparathyroidism, aluminum toxicity, hemolysis, malignancies,hematologic disorders, AIDS, pregnancy, and vitamin deficiency (3).Cytokines (IL-1, IL-6, interferon-γ, tumor necrosis factor), hepcidin,EpoR and the subsequent intracellular signaling have also beenidentified as potential regulators of EPO responsiveness (4, 5).Further, there is an interaction between IL-6 and hepcidin that isresponsible for hypoferremia that may limit ESA response (6, 7), andsoluble EpoR concentrations may be associated with EPO resistance in endstage renal disease (ESRD) (8, 9). To date, however, and despite theidentification of factors that may cause different patients to responddifferently to erythropoietic agents, biomarkers have yet to beidentified that allow a patient's response to an erythropoietic agent tobe effectively predicted.

SUMMARY

The presently-disclosed subject matter meets some or all of theabove-identified needs, as will become evident to those of ordinaryskill in the art after a study of information provided in this document.

This summary describes several embodiments of the presently-disclosedsubject matter, and in many cases lists variations and permutations ofthese embodiments. This summary is merely exemplary of the numerous andvaried embodiments, and mention of one or more representative featuresof a given embodiment is likewise exemplary. Such an embodiment cantypically exist with or without the feature(s) mentioned; likewise,those features can be applied to other embodiments of thepresently-disclosed subject matter, whether listed in this summary ornot. To avoid excessive repetition, this summary does not list orsuggest all possible combinations of such features.

The presently-disclosed subject matter includes methods and kits forpredicting a response to an erythropoietic agent in a subject. In someembodiments of the presently-disclosed subject matter, a method forpredicting a response to an erythropoietic agent in a subject isprovided that includes the steps of: (a) providing a biological samplefrom the subject; and (b) determining an amount in the sample of atleast one peptide selected from the group consisting of SEQ ID NOS:1-17. In certain embodiments, the amount of the at least one peptideselected from SEQ ID NOS: 1-17, if present in the sample, is thencompared to a control level of the at least one peptide and, if there isa measurable difference in the amount of the at least one peptide in thesample as compared to the control level, the comparison can be used topredict whether a subject is going to have a good response or a poorresponse to the erythropoietic agent.

In some embodiments, the methods of the presently-disclosed subjectmatter further comprise the step of determining whether there is ameasureable difference in the amount of the at least one peptide in thesample as compared to the amount of the at least one peptide in a knowngood responder and/or a known poor responder, as an indicator of thesubject's predicted response. In some embodiments, an amount of theerythropoietic agent administered to the subject is selected or modifiedbased on the determined amount of the at least one peptide.

In some embodiments of the diagnostic methods described herein, the atleast one peptide is selected from the group consisting of SEQ ID NOS:1-14, and the subject is predicted to have a good response to theerythropoietic agent if there is a measurable difference in the amountof the at least one peptide selected from SEQ ID NOS: 1-14 as comparedto the control level of the peptide. In other embodiments, the at leastone peptide is selected from the group consisting of SEQ ID NOS: 15-17,and the subject is predicted to have a poor response to theerythropoietic agent if there is a measurable difference in the amountof the at least one peptide selected from SEQ ID NOS: 15-17 as comparedto the control level of the peptide.

In other embodiments of the presently-disclosed subject matter, a methodfor determining whether to modify the amount of an erythropoietic agentbeing administered to the subject is provided. In some embodiments, anexemplary method for determining whether to modify an amount of anerythropoietic agent that is administered to a subject includes thesteps of: (a) providing a series of biological samples over a timeperiod from the subject; and (b) analyzing the series of biologicalsamples to determine an amount in each of the biological samples of atleast one peptide selected from the group consisting of SEQ ID NOS:1-17. In some embodiments, the method further comprises comparing anymeasurable change in the amounts of the at least one peptide in each ofthe biological samples to thereby determine whether to modify the amountof the erythropoietic agent administered to the subject. In someembodiments, the series of biological samples comprises a firstbiological sample collected prior to modifying the amount of theerythropoietic agent administered to the subject and a second biologicalsample collected after modifying the amount of the erythropoietic agentadministered to the subject.

In some embodiments of the presently-disclosed methods for determiningwhether to modify the amount of an erythropoietic agent beingadministered to the subject, the at least one peptide is selected fromthe group consisting of SEQ ID NOS: 1-14, and the amount of theerythropoietic agent administered to the subject is decreased if thereis a measurable difference in the amount of the at least one peptideselected from SEQ ID NOS: 1-14 as compared to the control level. Inother embodiments, the at least one peptide is selected from the groupconsisting of SEQ ID NOS: 15-17, and the amount of the erythropoieticagent administered to the subject is increased if there is a measurabledifference in the amount of the at least one peptide selected from SEQID NOS: 15-17 as compared to the control level.

In some embodiments of the methods described herein, the subject haskidney disease, anemia, or cancer. Further, in some embodiments, thebiological sample from the subject comprises blood, plasma, serum, orurine. In some embodiments, the subject is human.

With regard to the step of determining an amount in the sample of atleast one peptide, in some embodiments, determining the amount in thesample of the at least one peptide comprises applying the biologicalsample to a device capable of affecting detection of the at least onepeptide. In some embodiments, determining the amount in the sample ofthe at least one peptide comprising using mass spectrometry (MS)analysis, immunoassay analysis, or both to determine the amount of theat least one peptide. The MS analysis can comprise, in some embodiments,matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF)MS analysis. In some embodiments, the immunoassay analysis comprises anenzyme-linked immunosorbent assay (ELISA).

In further embodiments of the presently-disclosed subject matter, anantibody or fragment thereof is provided that specifically recognizes apeptide selected from the group consisting of SEQ ID NOS: 1-17.

In still other embodiments of the presently-disclosed subject matter, akit for predicting a response to an erythropoietic agent is provided. Insome embodiments, a kit for predicting a response to an erythropoieticagent in a subject is provided that comprises one or more antibodies orfragments thereof that specifically recognize a peptide selected fromthe group consisting of SEQ ID NOS: 1-17. In some embodiments of thekits, the antibody is bound to a substrate and, in some embodiments, thekits can further include instructions for using the kit. In someembodiments, a plurality of different antibodies can be included in thekits such that each kit includes a number of antibodies capable ofdetecting a number of the peptides of SEQ ID NOS: 1-17.

Further features and advantages of the presently-disclosed subjectmatter will become evident to those of ordinary skill in the art after astudy of the description, figures, and non-limiting examples in thisdocument.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-1B are graphs showing serum C-reactive protein (CRP; FIG. 1A)and hepcidin (FIG. 1B) concentrations in subjects, where theconcentrations are displayed according to group (good vs. poorresponder) and gender.

FIGS. 2A-2B are graphs showing serum concentrations of IL-6 (FIG. 2A),IL-7 (FIG. 2B), IL-8 (FIG. 2C), IL-10 (FIG. 2D), and TNF-alpha (FIG. 2E)found in sample from subjects, where the concentrations are displayedaccording to group (good vs. poor responder) and gender.

FIGS. 3A-3B are graphs showing a comparison of the size of the foldchange in peptide abundance in good- to poor-responder serum samples tothe statistical significance level, where, for peptides with t-testp-values less than 0.05, the ratio of the abundance (extracted from a3-minute window of the LC-MALDI-TOF MS ion chromatogram) for the EPOgood- to poor-responders were calculated, and where the t-test and ratiodata are plotted using log-log graphing for each significant peptidefrom the freely soluble serum peptide and protein bound serum peptidefractions with the shaded regions denoting masses with a p-value lessthan 0.001.

FIGS. 4A-4E are graphs (FIGS. 4A-4D) and an image of an immunoblot (FIG.4E) showing the distribution of serum oncostatin M receptor β chain(OSMRβ) fragments and protein levels associated with erythropoieticagent responsiveness, where peptide abundance data was extracted fromaligned mass spectrometry data sets and peptide spectral abundance wascalculated from the MS ion cluster area (10), and where vertical scatterplots (mean±SEM) for the differences in serum abundance for three OSMRβfragments (FIGS. 4A-4C) and for densitometry measurements of circulatingOSMRβ (FIGS. 4C-4D) illustrate significant differences in abundancebetween good responder and poor responder groups.

FIGS. 5A-5D are graphs (FIGS. 5A-5B) and an image of an immunoblot(FIGS. 5C-5D) showing the distribution of a serum cysteine/histidinerich 1 (CYHR1) fragment and protein levels associated witherythropoietic agent responsiveness, where peptide abundance data wasextracted from aligned MS data sets and peptide spectral abundance wascalculated from the MS ion cluster area, where vertical scatter plots(mean±SEM) for the differences in serum abundance for one CYHR1 fragment(FIG. 5A) and for densitometry measurements of circulating OSMRβ (FIGS.5B-5C) illustrate significant differences in abundance between goodresponder and poor responder groups, and where the specificity of theCYHR1 antibody was confirmed using immunogen competition experiments(FIG. 5D) where the primary antibody was pre-incubated with a 10-foldexcess of synthetic immunogen before applying it to a freshly blottedand blocked membrane.

BRIEF DESCRIPTION OF THE SEQUENCE LISTING

SEQ ID NOS: 1-10 are amino acid sequences of peptide fragments of afibrinogen alpha chain protein;

SEQ ID NO: 11 is an amino acid sequence of a peptide fragment of afibrinogen beta chain protein;

SEQ ID NO: 12 is an amino acid sequence of a peptide fragment of acoagulation factor XIII A chain protein;

SEQ ID NO: 13 is an amino acid sequence of a peptide fragment of acysteine and histidine-rich protein 1 protein;

SEQ ID NO: 14 is an amino acid sequence of a peptide fragment of acomplement C3 protein; and

SEQ ID NOS: 15-17 are amino acid sequences of peptide fragments of anoncostatin-M specific receptor subunit beta protein.

DESCRIPTION OF EXEMPLARY EMBODIMENTS

The details of one or more embodiments of the presently-disclosedsubject matter are set forth in this document. Modifications toembodiments described in this document, and other embodiments, will beevident to those of ordinary skill in the art after a study of theinformation provided in this document. The information provided in thisdocument, and particularly the specific details of the describedexemplary embodiments, is provided primarily for clearness ofunderstanding and no unnecessary limitations are to be understoodtherefrom. In case of conflict, the specification of this document,including definitions, will control.

While the following terms are believed to be well understood by one ofordinary skill in the art, definitions are set forth to facilitateexplanation of the presently-disclosed subject matter.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which the presently-disclosed subject matter belongs.Although any methods, devices, and materials similar or equivalent tothose described herein can be used in the practice or testing of thepresently-disclosed subject matter, representative methods, devices, andmaterials are now described.

Following long-standing patent law convention, the terms “a”, “an”, and“the” refer to “one or more” when used in this application, includingthe claims. Thus, for example, reference to “a peptide” includes aplurality of such peptides, and so forth.

Unless otherwise indicated, all numbers expressing quantities ofingredients, properties such as reaction conditions, and so forth usedin the specification and claims are to be understood as being modifiedin all instances by the term “about”. Accordingly, unless indicated tothe contrary, the numerical parameters set forth in this specificationand claims are approximations that can vary depending upon the desiredproperties sought to be obtained by the presently-disclosed subjectmatter.

As used herein, the term “about,” when referring to a value or to anamount of mass, weight, time, volume, concentration or percentage ismeant to encompass variations of in some embodiments ±20%, in someembodiments ±10%, in some embodiments ±5%, in some embodiments ±1%, insome embodiments ±0.5%, and in some embodiments ±0.1% from the specifiedamount, as such variations are appropriate to perform the disclosedmethods.

The terms “polypeptide”, “protein”, and “peptide”, which are usedinterchangeably herein, refer to a polymer of the 20 protein aminoacids, including modified amino acids (e.g., phosphorylated, glycated,etc.) and amino acid analogs, regardless of size or function. Although“protein” is often used in reference to relatively large polypeptides,and “peptide” is often used in reference to small polypeptides, usage ofthese terms in the art overlaps and varies. The term “peptide” as usedherein refers to peptides, polypeptides, proteins and fragments ofproteins, unless otherwise noted. The terms “protein”, “polypeptide” and“peptide” are used interchangeably herein when referring to a geneproduct and fragments thereof. Thus, exemplary polypeptides include geneproducts, naturally occurring proteins, homologs, orthologs, paralogs,fragments and other equivalents, variants, fragments, and analogs of theforegoing.

The terms “polypeptide fragment” or “fragment”, when used in referenceto a polypeptide, refers to a polypeptide in which amino acid residuesare absent as compared to the full-length polypeptide itself, but wherethe remaining amino acid sequence is usually identical to thecorresponding positions in the reference polypeptide. Such deletions canoccur at the amino-terminus or carboxy-terminus of the referencepolypeptide, or alternatively both. A fragment can retain one or more ofthe biological activities of the reference polypeptide. In someembodiments, a fragment can comprise a domain or feature, and optionallyadditional amino acids on one or both sides of the domain or feature,which additional amino acids can number from 5, 10, 15, 20, 30, 40, 50,or up to 100 or more residues. Further, fragments can include asub-fragment of a specific region, which sub-fragment retains a functionof the region from which it is derived. When the term “peptide” is usedherein, it is intended to include the full-length peptide as well asfragments of the peptide. Thus, an identified fragment of a peptide(e.g., by mass spectrometry) is intended to encompass the fragment aswell as the full-length peptide. As such, determining an amount of abiomarker in a sample can include determining an amount of thefull-length biomarker polypeptide, modified variants, and/or fragmentsthereof.

Current biomarkers of hemoglobin (Hb) response to erythropoietic agentsare primarily measurements of inflammation and iron availability. Whilethese measurements remain important factors in monitoring a particularindividual's response to an erythropoietic agent, the measurements donot address all of the aspects of a response to an erythropoietic agentand, as such, they can not effectively be used to predict whether anindividual will exhibit a good or poor response to the administration ofan erythropoietic agent. To that end, the presently-disclosed subjectmatter is based, at least in part, on the discovery of peptidebiomarkers that can be obtained from a biological sample from a subjectand effectively utilized to predict the subject's response to anerythropoietic agent and to determine whether to administer a specificdose of an erythropoietic agent to that subject or to modify a dose thatthe subject is already receiving.

In some embodiments, the presently-disclosed subject matter thusprovides methods and systems for predicting a response to anerythropoietic agent in a subject, and for determining whether to modifyan amount of an erythropoietic agent being administered to a subject, byidentifying at least one biomarker in a biological sample from asubject. In some embodiments, the at least one biomarker is a peptidebiomarker, or a fragment thereof, selected from the following Table 1:

TABLE 1 Peptide Biomarkers for Prediction ofResponses to Erythropoietic Agents. SEQ Paragon ID Observed Amino AcidPost-translational Mascot Unused NO: Mass (m/z) Parent Protein NameAmino Acid Sequence Modification MOWSE Score Increase Serum AbundunceFreely Soluble with Hyper-response  1 1194.521 Fibrinogen alpha chainD.SGEGDFLAEGGGV.R  46 14  2 1399.623 Fibrinogen alpha chainS.GEGDFLAEGGGVR.G (N-term + 136.16) 116^($)  3 1463.656Fibrinogen alpha chain A.DSGEGDFLAEGGGVR.G 14.0  4 1481.653Fibrinogen alpha chain A.DSGEGDFLAEGGGVR.G Phe → Tyr@7 132 14  51534.689 Fibrinogen alpha chain D.ADSGEGDFLAEGGGVR.G 14.0  6 1534.689Fibrinogen alpha chain D.SGEGDFLAEGGGVR.G (N-term + 183.98)  93^($)  72466.054 Fibrinogen alpha chain S.SSYSKQFTSSTSYNRGDS  55 14 TFES.K  82553.101 Fibrinogen alpha chain K.SSSYSKQFTSSTSYNRGD  75 14 STFES.K  92768.252 Fibrinogen alpha chain K.SSSYSKQFTSSTSYNRGD 115 14 STFESKS.Y 102931.292 Fibrinogen alpha chain K.SSSYSKQFTSSTSYNRGD  63 14 STFESKSY.K11 1552.673 Fibrinogen beta chain S.QGVNDNEEGFFSAR.G Gln → pyro- 27Glu@N-term Serum Protein Bound 12 1210.582 Coagulation factorM.SETSRTAFGGR.R Acetyl@N-term  2.0 XIII A Chain 13 1488.800Cysteine and histidine- L.SHLVLGVVSLHAAVS.T  1.3¶¶ rich protein 1 141504.82 Complement C3 G.SPMYSIITPNILR.L  46  2 Freely Soluble 151273.633 Oncostatin-M specific E.NKEVEEERIAG.T  50  2.1receptor subunit beta 16 1549.744 Oncostatin-M specificE.NKEVEEERIAGTE.G (C-term + 45.99) ^(#)  48 receptor subunit beta 171664.801 Oncostatin-M specific E.NKEVEEERIAGTE.G (T(12) + 161.02)  49receptor subunit beta **Amino acid sequence is presented using ParisConvention guidelines for presenting proteomics data. The proteolyticexcision sites are offset with periods. Amino acids within periodscomprise the amino acid sequence for the observed peptide biomarker.^($)Matrix Science Mascot MOWSE Score following post-hoc error tolerantanalysis. ^(#) Additional mass of 45.99 reflects addition of two sodiumions. ¶Protein Pilot Paragon Confidence Interval scoring for the proteinand the peptides listed were 99% (Unused Score > 2.0) with simultaneousadjustment for decoy data base analysis and removal of false positiveidentifications. ¶¶Protein Pilot Paragon Confidence Interval scoring was95% (Unused Score = 1.3) with simultaneous adjustment for decoy database analysis and removal of false positive identifications.

In some embodiments of the exemplary human biomarkers included in Table1 above, the core amino acid sequence can optionally be detected withadditional masses added to the N- or C-terminus of the recited peptides.For example, in some embodiments, an additional mass (m/z) of about136.16 can be added to the α-amino group of the N-terminus glycineresidue in SEQ ID NO: 2. As another example, in certain embodiments, thesequence of SEQ ID NO: 6 can further include a mass of about 183.98 thatis added to the N-terminal serine residue.

Further, the exemplary human biomarkers included in Table 1 above arenot intended to limit the present subject matter to human polypeptidebiomarkers or mRNA biomarkers only. Rather, the present subject matteris intended to encompass biomarkers across animal species that arecapable of being used to predict a response to an erythropoietic agentin a subject. In addition, standard gene/protein nomenclature guidelinesgenerally stipulate human gene name abbreviations are capitalized anditalicized and protein name abbreviations are capitalized, but notitalicized. Further, standard gene/protein nomenclature guidelinesgenerally stipulate mouse, rat, and chicken gene name abbreviationsitalicized with the first letter only capitalized and protein nameabbreviations capitalized, but not italicized. In contrast, thegene/protein nomenclature used herein when referencing specificbiomarkers uses all capital letters for the biomarker abbreviation, butis intended to be inclusive of genes (including mRNAs and cDNAs) andproteins across animal species.

A “biomarker” is a molecule useful as an indicator of a biologic statein a subject. With reference to the present subject matter, thebiomarkers disclosed herein can be polypeptides that exhibit a change inexpression or state, and which can be correlated to and used to predicta response to an erythropoietic agent in a subject. In addition, thebiomarkers disclosed herein are inclusive of messenger RNAs (mRNAs)encoding the biomarker polypeptides, because measurement of a change inexpression of an mRNA can be correlated with changes in expression ofthe polypeptide encoded by the mRNA. As such, determining an amount of abiomarker in a biological sample is inclusive of determining an amountof a polypeptide biomarker and/or an amount of an mRNA encoding thepolypeptide biomarker either by direct or indirect (e.g., by measure ofa complementary DNA (cDNA) synthesized from the mRNA) measurement of themRNA.

In some embodiments of the presently-disclosed subject matter, a methodfor predicting a response to an erythropoietic agent in a subject isprovided. In some embodiments, the method comprises providing abiological sample obtained from a subject; and determining an amount inthe sample of at least one peptide selected from the group consisting ofSEQ ID NOS: 1-17 (i.e., the peptide biomarkers of Table 1). In someembodiments, the method further includes comparing the amount of the atleast one peptide in the sample, if present, to a control level of theat least one peptide, wherein the subject is predicted to have a goodresponse or a poor response to the erythropoietic agent if there is ameasureable difference in the amount of the at least one peptide in thesample as compared to a control level. In other embodiments, the methodfurther includes determining whether there is a measurable difference inthe amount of the at least one peptide in the sample as compared to theamounts of the peptides in a good responder and/or a poor responder asan indication of the subject's predicted response to the erythropoieticagent.

The terms “erythropoietic agent,” “erythropoiesis stimulating agents,”or “ESA(s)” are used interchangeably herein to refer to agents that arecapable of stimulating red blood cell production. As such, the term“erythropoietic agent” is inclusive of erythropoietin (EPO), but is alsoinclusive of iron or iron attached to various carrier proteins, as wellas various pharmaceutical preparations of EPO including, but not limitedto, Epoetin, Procrit or Epogen or Eprex or ReliPoietin or Epokine orShanpoietin (epoetin-alpha), Epoetin-alpha, neoRecormon or Betapoietin(epoetin-beta), Epoetin-beta, Aranesp (darbepoetin), Darbopoetin alfa,Mircera (methoxy polyethylene glycol-epoetin beta), Methoxy PolyethyleneGlycol-Epoetin beta, Dynepo (Epoetin delta), Epoetin delta, Hematide(peginesatide) and formulations of pharmaceutical preparations such asHIF PHI (HIF prolyl hydroxylase inihibor FG-2216 by FibroGen, Inc.) thateffect the biological activity of prolyl hydroxylation including, butnot limited to, hypoxia inducible factor alpha or beta subunits.

The terms “predicting” and “predict,” as used herein, refer to methodsby which the skilled artisan can estimate and even determine how asubject will respond to the administration of an erythropoietic agent,including the administration of a particular dose of erythropoietin. Theskilled artisan often makes such a prediction on the basis of one ormore indicators, such as, for example, a biomarker of thepresently-disclosed subject matter, the amount (including the presenceor absence) of which is indicative of how the subject will respond tothe erythropoietic agent. In some embodiments, and as described infurther detail below, the presence or absence of the biomarker can beused to categorize a subject as one who will display a positive or asufficient response to the erythropoietic agent (i.e., a “goodresponder”) or as one who will display a negative or an insufficientresponse to the erythropoietic agent (i.e., a poor responder).

In some embodiments of the presently-disclosed subject matter, whether asubject is a good responder or a poor responder is determined by using acalculated average EPO response index (ERI), which is defined as theerythropoietic agent (e.g., erythropoietin) dose divided by theresulting hemoglobin after 1-month of treatment with the agent. In someembodiments, a sufficient response to an erythropoietic agent (e.g.,erythropoietin) can be described with reference to a subject whoachieves a hemoglobin (Hb) of 11 grams per deciliter (g/dL) with a doseof 15,000 Units erythropoietin per week (ERI of 1.36 g/dL per 1000U/week). In such embodiments, subjects that respond below an ERI of 1.36g/dL per 1000 U/week can be categorized as good responders, while thosesubjects that respond above an ERI of 1.36 g/dL per 1000 U/week can becategorized as poor responders.

In some embodiments, along with a qualitative assessment of whether asubject will display a good or a poor response to an erythropoieticagent, it is also important to quantify how well a particular subjectwill respond to the administration of an erythropoietic agent in orderto plan the most effective therapy. If a more accurate assessment can bemade of a particular subject's ability to respond to an erythropoieticagent, appropriate therapy, and in some instances less severe therapy,for the subject can be chosen such that the subject can be administereda controlled dose of the erythropoietic agent in a regulated manner. Inthis regard, measurement of biomarker levels disclosed herein (e.g.,peptide biomarkers of SEQ ID NOS: 1-17) can be useful in order tocategorize subjects according to how well they will respond to anerythropoietic agent to determine who will benefit from particulartherapies and doses, and differentiate from other subjects wherealternative or additional therapies can be more appropriate. As such,“making a prediction” or “predicting”, as used herein, is furtherinclusive of determining the level at which a particular subject willrespond to an erythropoietic agent, which can allow for predicting aclinical outcome (with or without medical treatment), selecting anappropriate treatment (or whether treatment would be effective), ormonitoring a current treatment and potentially changing the treatment,based on the measure of predictive biomarker levels disclosed herein.

Of course, the term “predict” does not refer to the ability to predictwhether a subject will display a good or poor response to anerythropoietic agent with 100% accuracy. Instead, the skilled artisanwill understand that the term “predict” refers to an increasedprobability that a certain course or outcome will occur; that is, that acourse or outcome is more likely to occur in a subject exhibitingcertain levels of a biomarker, when compared to those individualsexhibiting control levels of the biomarkers. For example, in individualsexpressing the biomarkers (e.g., expressing them at an increased level),the chance of a given response may be about 3%. In certain embodiments,a prediction is about a 5% chance of a given outcome, about a 7% chance,about a 10% chance, about a 12% chance, about a 15% chance, about a 20%chance, about a 25% chance, about a 30% chance, about a 40% chance,about a 50% chance, about a 60% chance, about a 75% chance, about a 90%chance, or about a 95% chance.

The skilled artisan will also understand that associating a predictivebiomarker with a predisposition to a particular response is astatistical analysis. For example, a biomarker level (e.g., quantity ofexpression in a sample) of greater than a control level in someembodiments can signal that a subject is more likely to respond to theadministration of an erythropoietic agent than subjects with a levelless than or equal to the control level, as determined by a level ofstatistical significance. Statistical significance is often determinedby comparing two or more populations, and determining a confidenceinterval and/or a p value. See, e.g., Dowdy and Wearden, Statistics forResearch, John Wiley & Sons, New York, 1983, incorporated herein byreference in its entirety. Preferred confidence intervals of the presentsubject matter are 90%, 95%, 97.5%, 98%, 99%, 99.5%, 99.9% and 99.99%,while preferred p values are 0.1, 0.05, 0.025, 0.02, 0.01, 0.005, 0.001,and 0.0001.

In other embodiments, a threshold degree of change in the level of abiomarker of the presently-disclosed subject matter can be established,and the degree of change in the level of the biomarker in a biologicalsample can simply be compared to the threshold degree of change in thelevel. A preferred threshold change in the level for markers of thepresently disclosed subject matter is about 5%, about 10%, about 15%,about 20%, about 25%, about 30%, about 50%, about 75%, about 100%, andabout 150%. In yet other embodiments, a “nomogram” can be established,by which a level of a biomarker of the presently-disclosed subjectmatter can be directly related to an associated disposition towards agiven response to an erythropoietic agent. The skilled artisan isacquainted with the use of such nomograms to relate two numeric valueswith the understanding that the uncertainty in this measurement is thesame as the uncertainty in the marker concentration because individualsample measurements are referenced, not population averages.

In some embodiments of the presently-disclosed subject matter, multipledeterminations of one or more peptide biomarkers can be made, and atemporal change in the biomarker can be used to determine whether tomodify an amount of an erythropoietic agent that is being administeredto the subject. In such an embodiment, for example, the levels ofbiomarkers may decrease or increase over time indicating that thesubject's response to the erythropoietic agent is changing and that theamount of erythroipoietic agent being administered to the subject shouldbe modified (i.e., changed) as well. Thus, the presently-disclosedsubject matter provides, in some embodiments, a method for determiningwhether to modify an amount of an erythropoietic agent beingadministered to a subject. In some embodiments, the method comprisesdetermining an amount of at least one biomarker associated with aresponse to an erythropoietic agent, such as for example at least onebiomarker included in Table 1 (i.e., SEQ ID NOS: 1-17), in biologicalsamples collected from the subject at a plurality of different timepoints and comparing the amounts of the at least one peptide in thesamples collected at different time points. For example, a first timepoint can be selected and a second later time point can be selected. Oneor more biomarker levels can be measured in biological samples taken atthe different time points and qualitative and/or quantitativedifferences noted. A change in the amounts of the biomarker levels fromthe first and second samples can be correlated with a change in theresponse to an erythropoietic agent in a subject (e.g., changes in thelevels of red blood cells or changes in hemoglobin concentrations) andcan then be used to determine whether the amount of the erythropoieticagent being administered to the subject should be modified.

The term “modify,” and grammatical variations thereof, is used herein torefer to any changes or adjustments that can be made to the dose of anerythropoietin agent being administered to a subject. Determination andadjustment of a dose of an erythropoietic agent, as well as evaluationof when and how to make such adjustments, are known to those of ordinaryskill in the art of medicine.

The terms “correlated” and “correlating,” as used herein in reference tothe use of the presently-disclosed biomarkers, refer to comparing thepresence or quantity of the biomarker in a subject to its presence orquantity in subjects known to display a particular response to anerythropoietic agent, i.e. “good responders” or “poor responders.” Forexample, a biomarker level in a biological sample can be compared to alevel known to be associated with a specific response to anerythropoietic agent. The sample's biomarker level is said to have beencorrelated with the level of response that the subject will display tothe erythropoietic agent; that is, the skilled artisan can use thebiomarker level to determine whether the subject will be a good or apoor responder to the erythropoietic agent, and administer anappropriate dose of the agent to the subject. For example, based on thelevel of the biomarker and its comparison with a level of the biomarkerknown to be associated with a poor response, the skilled artisan maydetermine that the subject is a poor responder to erythropoietic agentsand administer an increased dose of the agent to the subject.Alternatively, a sample's biomarker level can be compared to a controlmarker level known to be associated with a good response to theerythropoietic agent, and the amount of erythropoietic agentadministered to the subject can be modified (e.g., decreased)accordingly.

With regard to the step of providing a biological sample from thesubject, the term “biological sample” as used herein refers to any bodyfluid or tissue potentially comprising the biomarkers of thepresently-disclosed subject matter (e.g., the peptide biomarkers ofTable 1), including, but not limited to, blood, plasma, serum, or urine.In some embodiments, for example, the biological sample can be a bloodsample, a serum sample, a plasma sample, or sub-fractions thereof.

With regard to the subjects from whom the sample is obtained, in someembodiments, the methods of the presently-disclosed subject matter areparticularly useful in subjects having a particular disease for whichthe administration of erythropoietic agents are typically recommended.For example, in some embodiments, the subject has kidney disease, anemia(e.g., anemia of chronic disease), or cancer, each of which are known tothose of ordinary skill in the art as diseases or conditions in whichthe amount of red blood cells and/or the concentrations of hemoglobinmay fall below normal levels and thus require the administration of anerythropoietic agent.

“Kidney disease,” as used herein refers to an acute or chronic injury toat least one kidney of a subject, and in particular renal tubular cellinjury. Kidney injury can be confirmed by any of a number of measurablecriteria known in the art, including but not limited to measurement ofthe level of microalbuminuria (MA) and renal function decline (e.g., bymeasuring glomerular filtration rate (GFR)) in a subject.

The term “anemia” is used herein to refer to a decrease in the amount ofred blood cells in a subject and/or a decrease in the amount ofhemoglobin in a subject as compared those exhibiting normal levels ofred blood cells or hemoglobin. A decrease in the amount of red bloodcells in a subject or a decrease in the amount of hemoglobin can bemeasured using any number of criteria and methods known to those orordinary skill in the art. In some embodiments, the anemia that isobserved in the subject is anemia of chronic disease, or anemia ofinflammation, which is frequently observed during chronic illness (e.g.,certain forms of kidney disease), and may be the result of the body of asubject's production of hepcidin or other regulators of iron metabolism.

The term “cancer” is used herein to refer to all types of cancer orneoplasm or malignant tumors found in animals, including leukemias,carcinomas, melanoma, and sarcomas. Examples of cancers are cancer ofthe brain, bladder, breast, cervix, colon, head and neck, kidney, lung,non-small cell lung, mesothelioma, ovary, prostate, sarcoma, stomach,uterus and Medulloblastoma.

Turning now to the step of identifying one or more biomarkers in thebiological sample, various methods and devices known to those skilled inthe art can be used to identify the one or more biomarkers in theprovided biological sample. In some embodiments, the methods of thepresently-described subject matter further comprise the step of applyingthe biological sample to a device capable of affecting detection of theat least one peptide. For example, as described in further detail below,in some embodiments, a technician can provide a biological sample (e.g.,select or pick up) and can then apply that sample to a mass spectrometrydevice to determine an amount of biomarkers in the provided sample.

In some embodiments, determining the amount of biomarkers in samplescomprises using an RNA measuring assay to measure mRNA encodingbiomarker polypeptides in the sample and/or using a protein measuringassay to measure amounts of biomarker peptides in the sample.

In certain embodiments, the amounts of biomarkers can be determined byprobing for mRNA of the biomarker in the sample using any RNAidentification assay known to those skilled in the art. Briefly, RNA canbe extracted from the sample, amplified, converted to cDNA, labeled, andallowed to hybridize with probes of a known sequence, such as known RNAhybridization probes (selective for mRNAs encoding biomarkerpolypeptides) immobilized on a substrate, e.g., array, or microarray, orquantitated by real time PCR (e.g., quantitative real-time PCR, such asavailable from Bio-Rad Laboratories, Hercules, Calif., U.S.A.). Becausethe probes to which the nucleic acid molecules of the sample are boundare known, the molecules in the sample can be identified. In thisregard, DNA probes for one or more of nucleic acid sequences encoding apeptide biomarker of the presently-disclosed subject matter can beimmobilized on a substrate and provided for use in practicing a methodin accordance with the present subject matter.

With regard to determining amounts of biomarker polypeptides in samples,mass spectrometry and/or immunoassay devices and methods can be used tomeasure biomarker polypeptides in samples, although other methods areknown to those skilled in the art as well. See, e.g., U.S. Pat. Nos.6,143,576; 6,113,855; 6,019,944; 5,985,579; 5,947,124; 5,939,272;5,922,615; 5,885,527; 5,851,776; 5,824,799; 5,679,526; 5,525,524; and5,480,792, each of which is hereby incorporated by reference in itsentirety. Immunoassay devices and methods can utilize labeled moleculesin various sandwich, competitive, or non-competitive assay formats, togenerate a signal that is related to the presence or amount of ananalyte of interest. Additionally, certain methods and devices, such asbiosensors and optical immunoassays, can be employed to determine thepresence or amount of analytes without the need for a labeled molecule.See, e.g., U.S. Pat. Nos. 5,631,171; and 5,955,377, each of which ishereby incorporated by reference in its entirety.

Thus, in certain embodiments of the presently-disclosed subject matter,the biomarker peptides are analyzed using an immunoassay. The presenceor amount of a biomarker (e.g., a peptide biomarker of Table 1) can bedetermined using antibodies or fragments thereof specific for eachbiomarker and detecting specific binding. For example, in someembodiments, antibodies are provided that specifically recognize apeptide selected from SEQ ID NOS: 1-17. Such antibodies are inclusive ofantibodies that bind the full-length peptides or fragments thereof. Insome embodiments, the antibody is a monoclonal antibody. (For furtherexplanation and guidance with respect to the production and purificationof antibodies against a given epitope, see, e.g., Kohler and Milstein,Nature 256:495 (1975); U.S. Pat. Nos. 4,172,124; 4,350,683; 4,363,799;4,381,292; and 4,423,147. See also Kennett et al., Monoclonal Antibodies(1980) and references therein. Each of these references are incorporatedherein by this reference.)

Any suitable immunoassay can be utilized in accordance with thepresently-disclosed subject matter including, for example, enzyme-linkedimmunoassays (ELISA), radioimmunoassays (RIAs), competitive bindingassays, and the like. Specific immunological binding of the antibody tothe marker can be detected directly or indirectly. Direct labels includefluorescent or luminescent tags, metals, dyes, radionuclides, and thelike, attached to the antibody. Indirect labels include various enzymeswell known in the art, such as alkaline phosphatase, horseradishperoxidase and the like.

The use of immobilized antibodies or fragments thereof specific for themarkers is also contemplated by the presently-disclosed subject matter.The antibodies can be immobilized onto a variety of solid supports, suchas magnetic or chromatographic matrix particles, the surface of an assayplate (such as microtiter wells), pieces of a solid substrate material(such as plastic, nylon, paper), and the like. An assay strip can beprepared by coating the antibody or a plurality of antibodies in anarray on a solid support. This strip can then be dipped into the testbiological sample and then processed quickly through washes anddetection steps to generate a measurable signal, such as for example acolored spot.

In some embodiments, mass spectrometry (MS) analysis can be used aloneor in combination with other methods (e.g., immunoassays) to determinethe presence and/or quantity of the one or more biomarkers of interest(e.g., a peptide biomarker of Table 1) in a biological sample. In someembodiments, the MS analysis comprises matrix-assisted laserdesorption/ionization (MALDI) time-of-flight (TOF) MS analysis, such asfor example direct-spot MALDI-TOF or liquid chromatography MALDI-TOFmass spectrometry analysis. In some embodiments, the MS analysiscomprises electrospray ionization (ESI) MS, such as for example liquidchromatography (LC) ESI-MS. Mass analysis can be accomplished usingcommercially-available spectrometers, such as for example triplequadrupole mass spectrometers. Methods for utilizing MS analysis,including MALDI-TOF MS and ESI-MS, to detect the presence and quantityof biomarker peptides in biological samples are known in the art. See,e.g., U.S. Pat. Nos. 6,925,389; 6,989,100; 6,890,763; and, Merchant, etal. (Am J Physiol Renal Physiol 2008, 295, F1254-1258) for furtherguidance, each of which is incorporated herein by this reference.

Although certain embodiments of the method only call for a qualitativeassessment of the presence or absence of the one or more biomarkers inthe biological sample, other embodiments of the method call for aquantitative assessment of the amount of each of the one or morebiomarkers in the biological sample. Such quantitative assessments canbe made, for example, using one of the above mentioned methods, as willbe understood by those skilled in the art.

In certain embodiments of the method, a subject is predicted to have agood or a poor response to an erythropoietic agent upon identifying in abiological sample obtained from the subject certain of the biomarkersselected from SEQ ID NOS: 1-17. For example, in some embodiments, asubject is predicted to have a good response to the erythropoietic agentif there is a measureable difference (e.g., an increase) in the amountof one or more of the peptide biomarkers of SEQ ID NOS: 1-14 as comparedto a control level of those biomarkers. In some embodiments, the subjectis predicted to have a good response to the erythropoietic agent ifthere is a measurable difference (e.g., an increase) in the amount ofthe peptide of SEQ ID NO: 13. In other embodiments of the method, asubject is predicted to have a poor response to the erythropoietic agentif there is a measureable difference (e.g., an increase) in the amountof one or more of the peptide biomarkers of SEQ ID NOS: 15-17 ascompared to a control level of those biomarkers.

As noted herein above, in certain embodiments of the presently-disclosedmethods, it can be desirable to include a control sample that isanalyzed concurrently with the biological sample, such that the resultsobtained from the biological sample can be compared to the resultsobtained from the control sample. Additionally, it is contemplated thatstandard curves can be provided, with which assay results for thebiological sample can be compared. Such standard curves present levelsof protein marker as a function of assay units, i.e., fluorescent signalintensity, if a fluorescent signal is used. Using samples taken frommultiple donors, standard curves can be provided for control levels ofthe one or more markers in normal tissue.

It is also contemplated that the efficacy, accuracy, sensitivity, and/orspecificity of the method can be enhanced by probing for multiplebiomarkers in the biological sample. For example, in certain embodimentsof the method, the biological sample can be probed for the peptidebiomarker of SEQ ID NO: 13 and at least one marker selected from thepeptides of SEQ ID NOS: 15-17. For another example, the biologicalsample can be probed for 2-5 markers selected from the peptidebiomarkers of SEQ ID NOS: 1-17. For another example, the biologic samplecan be probed for 6-10 markers selected from the peptide biomarkers ofSEQ ID NOS: 1-17.

The analysis of biomarkers can be carried out separately orsimultaneously with additional markers within one test sample. Forexample, several biomarkers can be combined into one test for efficientprocessing of a multiple of samples and for potentially providinggreater predictive accuracy. In addition, one skilled in the art wouldrecognize the value of testing multiple samples (for example, atsuccessive time points) from the same subject. Such testing of serialsamples can allow the identification of changes in biomarker levels overtime. Increases or decreases in biomarker levels, as well as the absenceof change in biomarker levels, can provide useful information about thesubject's status that includes, but is not limited to, identifying anychanges in response to an erythropoietic agent over time, theappropriateness of drug therapies, the effectiveness of varioustherapies, and identification of the subject's outcome, including riskof future events.

The analysis of biomarkers can be carried out in a variety of physicalformats as well. For example, the use of microtiter plates or automationcan be used to facilitate the processing of large numbers of testsamples. Alternatively, single sample formats could be developed tofacilitate immediate treatment and diagnosis in a timely fashion, forexample, in ambulatory transport or emergency room settings.

As mentioned above, depending on the embodiment of the method,identification of the one or more markers can be a qualitativedetermination of the presence or absence of the biomarkers, or it can bea quantitative determination of the concentration of the biomarkers. Inthis regard, in some embodiments, the step of identifying the subject asbeing a good or a poor responder to an erythropoietic agent requiresthat certain threshold measurements are made, i.e., the levels of theone or more biomarkers in the biological sample exceed control levels.In certain embodiments of the method, the control level is anydetectable level of the biomarker. In other embodiments of the methodwhere a control sample is tested concurrently with the biologicalsample, the control level is the level of detection in the controlsample. In other embodiments of the method, the control level is basedupon and/or identified by a standard curve. In other embodiments of themethod, the control level is a specifically identified concentration, orconcentration range. As such, the control level can be chosen, withinacceptable limits that will be apparent to those skilled in the art,based in part on the embodiment of the method being practiced and thedesired specificity, etc.

Further provided, in some embodiments of the presently-disclosed subjectmatter, is a system for the analysis of biomarkers that comprisesantibodies having specificity for one or more markers associated with asubject's response to an erythropoietic agent, including the peptidebiomarkers of SEQ ID NOS: 1-17. Such a system can comprise devices andreagents for the analysis of at least one test sample. The system canfurther comprise instructions for using the system and conducting theanalysis. Optionally, the systems can contain one or more reagents ordevices for converting a marker level to a prediction of a response in asubject.

Still further provided, in some embodiments, are kits for predicting aresponse to an erythropoietic agent that comprise one or more antibodiesor fragments thereof that specifically recognize a peptide selected fromSEQ ID NOS: 1-17. In some embodiments, the one or more antibodies arebound to a substrate and, in some embodiments, the one or moreantibodies comprise a plurality of antibodies. In other embodiments, thekits further include instructions for using the kit, such asinstructions for using the kit to predict a response to anerythropoietic agent in a subject.

In yet further embodiments of the presently-disclosed subject matter, amethod for screening for a compound useful for increasing red blood cellproduction is provided that comprises: providing a first subject and asecond subject; administering a test compound to the second subject;obtaining a biological sample from the first subject and the secondsubject; determining an amount in the samples from the first subject andthe second subject of at least one peptide selected from SEQ ID NOS:1-17; and identifying the test compound as a compound useful forincreasing red blood cell production based on a measurable difference inthe amount of the at least one peptide in the sample of the secondsubject as compared to the first subject.

In further embodiments of the presently-disclosed subject matter, amethod for determining and/or monitoring an amount of an erythropoieticagent administered to a subject is provided that comprises obtaining abiological sample from a subject administered or suspected of beingadministered an erythropoietic agent; determining an amount in thesample of at least one peptide selected from the group consisting of SEQID NOS: 1-17; and comparing the amount of the at least one peptide inthe sample, if present, to a level of the at least one peptide known tobe associated with a particular dose of the erythropoietic agent tothereby determine and/or monitor the amount of the erythropoietic agentadministered to the subject. As would be recognized by those of ordinaryskill in the art, such a method can be useful in monitoringerythropoietic agent dosing of subjects, including illicit dosing bysubjects such as cyclists, Olympic athletes, and high school,collegiate, and/or professional athletes.

With respect to the presently-disclosed subject matter, a preferredsubject is a vertebrate subject. A preferred vertebrate is warm-blooded;a preferred warm-blooded vertebrate is a mammal. A preferred mammal ismost preferably a human. As used herein, the term “subject” includesboth human and animal subjects. Thus, veterinary therapeutic uses areprovided in accordance with the presently-disclosed subject matter. Assuch, the presently-disclosed subject matter provides for the diagnosisof mammals such as humans, as well as those mammals of importance due tobeing endangered, such as Siberian tigers; of economic importance, suchas animals raised on farms for consumption by humans; and/or animals ofsocial importance to humans, such as animals kept as pets or in zoos.Examples of such animals include but are not limited to: carnivores suchas cats and dogs; swine, including pigs, hogs, and wild boars; ruminantsand/or ungulates such as cattle, oxen, sheep, giraffes, deer, goats,bison, and camels; and horses. Also provided is the treatment of birds,including the treatment of those kinds of birds that are endangeredand/or kept in zoos, as well as fowl, and more particularly domesticatedfowl, i.e., poultry, such as turkeys, chickens, ducks, geese, guineafowl, and the like, as they are also of economic importance to humans.Thus, also provided is the treatment of livestock, including, but notlimited to, domesticated swine, ruminants, ungulates, horses (includingrace horses), poultry, and the like.

The practice of the presently disclosed subject matter can employ,unless otherwise indicated, conventional techniques of cell biology,cell culture, molecular biology, transgenic biology, microbiology,recombinant DNA, and immunology, which are within the skill of the art.Such techniques are explained fully in the literature. See e.g.,Molecular Cloning A Laboratory Manual (1989), 2nd Ed., ed. by Sambrook,Fritsch and Maniatis, eds., Cold Spring Harbor Laboratory Press,Chapters 16 and 17; U.S. Pat. No. 4,683,195; DNA Cloning, Volumes I andII, Glover, ed., 1985; Oligonucleotide Synthesis, M. J. Gait, ed., 1984;Nucleic Acid Hybridization, D. Hames & S. J. Higgins, eds., 1984;Transcription and Translation, B. D. Hames & S. J. Higgins, eds., 1984;Culture Of Animal Cells, R. I. Freshney, Alan R. Liss, Inc., 1987;Immobilized Cells And Enzymes, IRL Press, 1986; Perbal (1984), APractical Guide To Molecular Cloning; See Methods In Enzymology(Academic Press, Inc., N.Y.); Gene Transfer Vectors For Mammalian Cells,J. H. Miller and M. P. Calos, eds., Cold Spring Harbor Laboratory, 1987;Methods In Enzymology, Vols. 154 and 155, Wu et al., eds., AcademicPress Inc., N.Y.; Immunochemical Methods In Cell And Molecular Biology(Mayer and Walker, eds., Academic Press, London, 1987; Handbook OfExperimental Immunology, Volumes I-IV, D. M. Weir and C. C. Blackwell,eds., 1986.

The presently-disclosed subject matter is further illustrated by thefollowing specific but non-limiting examples.

EXAMPLES Materials and Methods for Examples 1-5

Human Subjects.

The research protocol conformed to the Declaration of Helsinki andinformed consent was obtained from each subject prior to participationin the study. The study was approved by the Institutional Review Boardsfor both the University of Louisville and the Louisville VeteransAdministration Medical Center. Subjects were identified forparticipation in this study by determining their EPO responsiveness fromdose and response data. EPO dose and hemoglobin data were collected overa 5 month period of treatment for all in-center hemodialysis patients inthe Kidney Disease Program hemodialysis unit. For each combination ofEPO dose and hemoglobin, an EPO response index (ERI) was calculated asthe EPO dose divided by the resulting hemoglobin 1 month later. Thesedata were averaged over the 5 months of collected data and a mean ERIand standard deviation were determined. The mean data were sorted inascending order and subjects for the normal response group were selectedfrom the lowest quintile group. Subjects for the resistant respondergroup were selected from the highest quintile group.

Subjects were asked to enroll based on their falling into either theupper or lower quintile and based on the absence of the followingexclusion criteria: subjects were excluded if they: were inadequatelydosed using an erythropoietic stimulating agent; were iron deficient;were anemic due to blood loss; had a chronic infection or inflammation;had secondary hyperparathyroidism; had aluminum toxicity; had hemolysis;had any malignancies or hematologic disorders; had AIDS; were pregnant;or, had a vitamin deficiency.

Samples and Sample Handling.

Subjects that passed the screening described above were asked to donate20 ml of blood for proteomic analysis following an informed consentprocess. The blood was collected in 2 to 10 ml red top vacutainer tubesprior to the initiation of the dialysis session, and was processedimmediately for serum separation and stored in 0.5 ml aliquots at −80°C. until analyzed.

Peptides were isolated from serum using Vivaspin 2 (Sartorius AG,Gottingen, Germany) spin filtration devices housing 5,000 Dalton nominalmolecular weight cutoff Hydrosart® (cellulosic) membranes (Sartorius AG,Gottingen, Germany). The sample handling approach yielded two lowmolecular weight peptidomic fractions: (a) freely soluble serumpeptides; and (b) peptides bound to serum proteins. In this approach,200 μL of each sample was loaded into Vivaspin 2 spin filtration deviceand spun at 3,000×g and 4° C. until 180 μL filtrate had been collectedin the retentate cup. The filtrate from this step (fraction 1) containedthe freely soluble peptides. The remaining 20 μL was diluted using 50 mMsodium phosphate/0.5 mM sodium EDTA, pH 7.4. The diluted sample was spunand concentrated down to 20 μL. The filtrate of this step was discarded.The process was repeated twice. The final sample was diluted back to 200μL with 50 mM sodium phosphate/0.5 mM sodium EDTA, pH 7.4. To thissolution, a stock solution of 8 M urea/0.89 M β-mercaptoethanol wasadded and used to denature and reduce all soluble protein. The finalconcentration of these reagents was 6 M urea and 0.667 Mβ-mercaptoethanol. This solution was then left to equilibrate for 2 h atroom temperature. Subsequently, the solution was spun at 3,000×g and 4°C. until at least 120 μL filtrate had been collected in the retentatecup. The filtrate from this step (fraction 2) contained the serumprotein bound peptides. These peptide fractions were lyophilized,redissolved into water, and then cleaned (concentrated and desalted)using a C18 reversed-phase cartridge (Michrom Bioresource, Auburn,Calif.) and acetonitrile and formic acid solutions.

Peptidomic Analyses.

Isolated peptides were analyzed using the method of Merchant, et al(26). Briefly, isolated peptides were analyzed using reversed-phase (RP)capillary-high performance liquid chromatography (capHPLC), roboticallyspotted onto archivable MALDI-TOF MS plates (Opti-TOF plates), andMALDI-TOF MS data was acquired using an Applied Biosystems (Foster City,Calif.) AB4700 Proteomics Analyzer operating in reflectron mode. LCMALDI-TOF MS ion chromatograms were constructed using Data Explorersoftware (Applied Biosystems, Foster City, Calif.) and then exported aspeak list text files and used for determination of differential peptideabundance. Additionally, individual LC-MS spectra were concatenated toproduce serum (FX1 or FX2) peptide LC-MALDI-TOF MS ion chromatogram pereach sample fraction analyzed.

Analysis of Serum Peptide Abundance.

Data from LC-MALDI-TOF MS ion chromatograms were extracted in the formof integrated signal area for the peptide isotopic series (area underthe curve, AUC) from the AB4700.t2d files using Data Explorer (AppliedBiosystems, Foster City, Calif.) software and exported to MarkerView(Applied Biosystems, Foster City, Calif.) software tochromatographically align and array the tabulated peptide peak listdata. Three LC fractions collected prior to initiating the RP elutiongradient and following re-equilibration of the column from 100% solventB to 100 solvent A were used to establish a null peptide mass list.These masses were subtracted from the aggregate data set. For purposesof statistical comparison, all peptide masses not appearing in a minimumof 80% (n=28) samples were excluded from further analysis. The remainingpeptides were compared by unpaired student's t-test. Peptides havingp-values less than 0.05 (p<0.05) were considered significant. Toillustrate selection of peptide for further analysis, the data forpeptides with a P-value<0.05 and a fold expression difference of 133%are illustrated. This approach provided a method to compare the level ofstatistical significance of differential protein or peptide abundanceand the fold over- or under-expression of proteins or peptides given aset of treatment conditions.

Computer Assisted Tandem-MS Data Analysis.

Candidate peptide m/z values selected from the statistical analyses werefurther investigated using tandem MS methods to better understand theirimportance in EPO responsiveness. The selected peptide masses were usedto establish a MALDI ion inclusion list and were fragmented using theAB4700 Proteomics Analyzer in TOF/TOF mode using 1KeV collision energy,collision induced dissociation (CID) and atmospheric gases (mediumpressure). Final fragmentation data were collected as averaged data from1500 laser shots.

The peptide fragmentation information was searched against theSwiss-Prot database using Matrix Science Mascot software (version 2.1)and using the Paragon algorithm of Protein Pilot to identify peptideswith the highest correlative amino acid sequence. The Mascot algorithmwas used to search the MS/MS datasets assuming no post-translationalmodifications. The Paragon algorithm was used in addition to the Mascotalgorithm due to the ability to simultaneously search the unassigneddata for amino acid substitutions (such as resulting from singlenucleotide polymorphisms) and for more than 130 post translationalmodifications. Criteria used for Mascot analysis were: (a) unconstrainedproteolytic search (no enzyme fragmentation criteria stipulated); (b)Swiss Protein database (20100119, 514212 sequences, 180900945 residues),Homo sapiens taxonomy (20355 sequences); (c) 0.15 Da mass accuracy forprecursor peptides; and, (d) 0.3 Da mass accuracy for peptide fragmention mass measurement. The resulting search yielded the likelihood ofpeptide homology or identity by a given total ion MOWSE (MolecularWeight Search) score of 47 or greater. Criteria used for the ProteinPilot (version 3.0, revision number 114732) and Paragon algorithm(version 3, revision 113442) analysis were: (a) uniprot_sprot.fastadatabase (revision of UniProt release 15.0); (b) an identification focusof both biological modifications and amino acid substitutions; and, (c)an Unused ProtScore (Conf)>: 0.05 and Competitor Error Margin(ProtScore)≧2.0. All Protein Pilot Paragon analyses were conducted usingsimultaneous analysis against a reversed SwissProt database andautomated filtering and retaining of peptides scoring with q-values(false discovery rate filter)≦0.10. Two oncostatin M receptor (OSMR)peptides were assigned a mass value that are consistent withmodifications including di-sodiation (+45.99 m/z) of peptide 1549.774and O-glucosamine (O-GlcN) modification (+161.02 m/z) of peptide1664.801 at threonine-539 using the Delta Mass database as a guide foridentity assignment. To further explore the likelihood of an O-GlcNmodification to Thr-539, the proposed peptide amino acid sequence plus30 residues on the flanking N- and C-terminal amino acid sequence wereanalyzed for the potential to have O-glycan modification using theNetOGlyc tool. The best general predictor score (G-score) exceeded 0.5for one threonine within this sequence. The G-score for this residue,Thr-539, exceeds the threshold value indicating a significant likelihoodof a site being modified by 0-glycosylation.

Immunoblot Analyses for Serum Protein Abundance.

In order to examine if the increased serum abundance of oncostatin Mreceptor beta subunit (OSMRβ) and of cysteine and histidine-richprotein-1 (CYHR1) fragments resulted from increased serum OSMRIβ andCYHR1 serum protein abundance, immunoblotting experiments using native(denaturing) and Laemmli (reducing/denaturing) sample buffers wereconducted. These analyses were conducted using polyclonal antibodiesraised to either full length human OSMRIβ (Abcam Inc., Cambridge, Mass.;cat. no. ab67805) and an internal epitope of human CYHR1 (Santa CruzBiotechnology, Inc., Santa Cruz, Calif.; sc-87664). The expression ofOSMRIβ and CYHR1 were examined using previously unthawed,contemporaneous aliquots of the serum sample set used for peptidomicanalyses.

In brief, serum samples were mixed with Laemmli Sample Buffer(Invitrogen, Carlsbad, Calif.) and β-mercaptoethanol was added asneeded. The samples were then heated to 70° C. for 10 min. Serum samplesfor OSMRIβ immunoblot analysis were separated using large format 10-20%Tris-Glycine gels (Jule Inc., Milford, Conn.) using tris-glycine-SDSbuffer. Serum samples for CYHR1 immunoblot analysis were separated usingsmall format NuPAGE 4-12% Bis-Tris gels (Invitrogen, Carlsbad, Calif.).The proteins were transferred to 0.45 μm nitrocellulose membrane(Whatman, Dassel, Germany) for 90 min at 30 V using Tris-NuPAGE transferbuffer (Invitrogen, Inc.) with 20% methanol for OSMRIβ immunoblotanalysis or 35 V at 150 mA for 35 Vh for CYHR1 immunoblot analysis.

After transfer, membranes used for OSMRIβ immunoblot experiments wereblocked with 1% skim milk for overnight, rinsed three times with TTBS(20 mM Tris-buffered saline/0.1% Tween 20) and incubated overnight withmouse anti-OSMRIβ antibody (1:1000 in TTBS) at 4° C. Membranes werewashed with TTBS. Following 1 hour incubation with horse radishperoxidase (HRP) conjugated secondary goat anti-mouse (1:10,000 in 5%milk), membranes were developed using West Pico Chemiluminescencesubstrate (Pierce, Rockford, Ill.). Membranes used for CYHR1 immunoblotexperiments were blocked with 5% skim milk for overnight, rinsed threetimes with TTBS (20 mM Tris-buffered saline/0.1% Tween 20) and incubatedovernight with goat anti-CYHR1 antibody (1:1,000 in 1% skim milk). HRPconjugated secondary goat anti-mouse (1:10,000 in 5% milk) membraneswere developed using West Pico Chemiluminescence substrate (Pierce,Rockford, Ill.). Films were imaged and densitometry measurementsacquired and compared. For CYHR1, additional peptide blockingexperiments using the protein immunogen were conducted to examinemonospecific binding of the antibody to antigen. The CYHR1 antibody (1μg) was incubated with 10 μg immunogen for 2 h at room temperature priorto application on the blocked nitrocellulose membrane.

Analysis of Serum Markers of Inflammation and Iron Status.

High sensitivity C-reactive protein (hs-CRP) measurements in patientserum samples were made using the Immulite 1000 High Sensitivity CRP kitby Siemens according to the manufacturer's guidelines. The Immulite 1000High Sensitivity CROP is a solid-phase chemiluminescent immunometricassay. The samples were diluted 1:101 with sample diluent then admixedand co-incubated for 30 minutes with solid phase bead (coated withprimary antibody (anti-CRP) capture reagent), monoclonal murine anti-CRPmonoclonal antibody and an alkaline phosphatase conjugated polyclonalrabbit anti-mouse antibody. The unbound patient sample and antibodycomplexes were removed by centrifugal wash. A chemiluminescent substratewas added to the test unit containing the bead and the signal generatedwas accepted as proportional to the bound enzyme.

Hepcidin-25 peptide measurements were made using the hepcidin-25 peptideenzyme immunoassay kit (EIA) S-1337 (Bachem Group, Torrance, Calif.) andusing the hepcidin-25 standard LEAP1 from Peptides International, Inc.(Louisville, Ky.) as a positive control. Serum was diluted 1:40 usingEIA buffer provided in kit, and 50 μl of both diluted serum samples andhepcidin-25 standard were added to the antiserum pre-coated plated for 2hours at room temperature. A 25 μl aliquot of biotinylated antiserum(tracer) was then added to the plated for competitive binding ofhepcidin overnight at 4° C. The captured biotinylated tracer wassubsequently bound by streptavidin-conjugated horseradish peroxidase(SA-HRP), and the intensity of color developed after adding thesubstrate TMB was inversely proportional to the concentration ofhepcidin in samples. The plate was read at 450 nm within 10 minutes ofadding stop solution. The R-squared was 0.9967 for LEAP1 positivecontrol peptide from 0-50 ng/ml using sigmoid regression while 0.9969for the hepcidin-25 standard provided in Bachem EIA kit. The coefficientof variation (CV) for a given hepcidin-25 concentration of 1.56 ng/mlwas 3.49% intra-assay and 3.43% inter-assay.

Statistical Analysis.

Statistical analysis was performed using PASW Statistics 18. Comparisonsof proportions, means, and means by gender were done by Pearson chisquare, t-test and analysis of variance, respectively. When multiplefragments of the same parent protein were analyzed a Bonferronicorrection was applied to address the problem of multiple comparisonsand the data were analyzed as the sum of all fragment abundances. Theability of the identified biomarkers to discriminate between groups wasanalyzed by ROC curve.

Example 1 Characteristics of the Study Population

The demographics of the subjects enrolled in the study are shown inTable 2. There were significant differences in ESA dose and average EPOresponse index (ERI), defined as the EPO dose divided by the resultinghemoglobin 1 month later, between the two study groups. The distributionof gender between groups was different but did not reach statisticalsignificance.

TABLE 2 Demographics of the Subject Population at Time of SampleCollection. Good Responder Poor Responder p-value Gender (m/f) 10/5 7/130.06* Hemoglobin (g/dL) 11.5 ± 0.6  11.2 ± 1.1  0.4 ESA Dose(U/treatment) 1467 ± 673  8392 ± 5833 <0.001 Total Iron Dose (mg)  953 ±1187 2035 ± 1604 0.035 Average ERI  0.11 ± 0.036 0.87 ± 0.51 <0.001 Kt/V1.53 ± 0.25 1.58 ± 0.27 0.5 Albumin (g/dL) 3.9 ± 0.3 3.8 ± 0.3 0.3Ferritin 767 ± 353 781 ± 416 0.9 Tsat (%) 30.5 ± 7.9  26.4 ± 16.5 0.4*Pearson Chi-Square

The subjects' serum was assayed for C-reactive protein, serum hepcidin,IL-6, IL-7, IL-8, IL-10 and TNF-α. These data are shown in FIGS. 1A-1Band FIGS. 2A-2E. The results of the statistical analysis are shown inTable 3. The only difference detected was an interaction between groupand gender in hepcidin, IL-6, and IL-8 where there appeared to beincreased serum levels of hepcidin, IL-6 and IL-8 in male hyporesponders.

TABLE 3 Statistical Analysis of the C-reactive Protein, Hepcidin andCytokine Data. p value Group Gender Interaction CRP 0.11 0.98 0.83Hepcidin 0.068 0.11 0.043 IL-6 0.71 0.18 0.018 IL-7 0.37 0.26 0.59 IL-80.57 0.58 0.046 IL-10 0.11 0.19 0.16 TNF-α 0.51 0.97 0.76

Example 2 Serum Peptide Analysis

Most peptides were of low abundance and infrequently observed across allsamples. A total of 939 freely soluble serum peptide masses wereobserved in 28 (82% of samples) or more serum samples. A total of 130masses were observed in all 34 samples. By t-test, 40 peptides wereobserved to be differentially abundant with significance at the p≦0.05level and 3 peptides at the p≦0.001 level (Table 4). A total of 558protein bound serum peptide masses were observed in 28 or more serumsamples. A total of 90 masses were observed in all 34 samples. Byt-test, 51 peptides were observed to be differentially abundant withsignificance at the p≦0.05 level and 9 peptides at the p≦0.001 level(Table 5). To graphically illustrate these data, plots of significance(P-value) versus serum abundance differences in good-responder topoor-responder (serum abundance ratio) for freely soluble (FIG. 3A) andprotein bound serum peptides (FIG. 3B) were constructed and annotated toindicate assignment of protein identities to respective data points.Mann and Kelleher have suggested fold-expression changes of 1.3 to 2.0or greater to be meaningful for MS-based proteomics experiments (10). Inthe present data, defined by peptides with p-values≦0.05, 38 freelysoluble serum peptides (95% total) and 50 protein bound serum peptides(98% total) demonstrated fold-abundance changes of 1.3 or greater. Forpurposes of emphasis, peptides estimated to have t-test P-values equalto or less than 0.001 are highlighted in FIG. 3 within the inset boxes.

TABLE 4 Peptides Identified as Differentially Abundant in Free SerumPeptidome (FX1). Peptide Mass to Chromatographic Observation Mean MeanFold Charge (C18 Reversed Frequency abundance abundance Abundance RatioPhase) Retention (Out of 34 (Good (Poor for (m/z) Time (min) Samples)Ttest Responder) Responder) [Good]/[Poor] Rank 1273.633 30 31 0.00005324278 62525 0.39 1 1664.801 35 28 0.000074 5489 21769 0.25 2 1552.673 3534 0.000436 80328 45578 1.76 3 2931.292 31 33 0.001107 115475 36514 3.164 852.885 38 32 0.003080 24214 16447 1.47 5 1549.774 36 28 0.003182 511012805 0.40 6 1393.727 35 34 0.003301 8937 16555 0.54 7 966.352 24 290.003479 12957 60430 0.21 8 2553.101 30 34 0.005737 90712 25069 3.62 91613.859 36 30 0.006602 3033 5162 0.59 10 1133.731 58 32 0.008351 152438843 1.72 11 2466.054 30 30 0.008865 22491 9077 2.48 12 1059.572 29 330.009226 125784 82602 1.52 13 987.643 56 28 0.013735 12726 7311 1.74 142768.252 29 34 0.016322 204777 67122 3.05 15 1481.653 30 34 0.01917662729 24318 2.58 16 957.631 59 32 0.019904 17417 10620 1.64 17 1279.84359 32 0.020860 9000 4946 1.82 18 1463.656 32 31 0.021406 26377 140291.88 19 1075.570 29 32 0.024467 48687 30613 1.59 20 1194.521 34 340.025702 35571 25570 1.39 21 1482.673 32 32 0.028119 5555 8952 0.62 22740.293 38 34 0.030052 1107047 945822 1.17 23 3277.546 30 31 0.03050717905 10006 1.79 24 1516.684 33 33 0.031415 15009 10275 1.46 25 1310.62532 33 0.033496 8381 13585 0.62 26 3215.618 30 28 0.034323 20032 104351.92 27 1276.530 34 30 0.037827 18636 11272 1.65 28 1147.739 60 310.038286 10695 6897 1.55 29 1534.689 33 33 0.039585 23402 15736 1.49 302265.983 23 31 0.040197 9547 4934 1.93 31 1415.691 37 30 0.041050 124907111 1.76 32 793.557 16 33 0.043446 7849 5970 1.31 33 1363.482 34 310.043627 17170 11572 1.48 34 977.476 29 30 0.043710 49410 22740 2.17 351128.476 34 33 0.045240 15648 23901 0.65 36 1563.914 38 34 0.045355 58389114 0.64 37 1399.623 35 34 0.045650 102327 54021 1.89 38 1242.471 38 280.045902 7936 5019 1.58 39 2249.981 23 33 0.046533 34037 19870 1.71 40

TABLE 5 Peptides Identified as Differentially Abundant in Bound SerumPeptidome (FX2). Peptide Chromatographic Mean Mean Fold Mass to (C18Reversed abundance abundance Abundance Charge Phase) RetentionObservation (Good (Poor for Ratio (m/z) Time (min) Frequency TtestResponder) Responder) [Good]/[Poor] Rank 1488.818 42 34 0.000001 14782350757 2.91 1 1117.625 25 32 0.000007 6133 22243 0.28 2 1668.902 40 340.000024 12583 3975 3.17 3 986.436 31 32 0.000122 7253 27593 0.26 41052.630 39 34 0.000125 53490 31517 1.70 5 1460.631 31 33 0.000245 1587895205 0.17 6 1896.805 33 32 0.000656 13706 5861 2.34 7 1015.591 22 310.000742 9538 19679 0.48 8 801.386 24 30 0.000923 4468 12803 0.35 92085.103 35 28 0.001303 4989 2451 2.04 10 1143.653 25 28 0.001558 434812782 0.34 11 1653.867 38 29 0.001888 5772 3520 1.64 12 833.271 35 340.001980 92371 52666 1.75 13 752.374 33 34 0.003486 181889 105978 1.7214 1575.838 40 32 0.003892 4826 2666 1.81 15 1812.849 29 34 0.00501510765 6936 1.55 16 898.422 28 33 0.005278 27041 15130 1.79 17 1476.62731 30 0.005857 2768 6520 0.42 18 921.519 33 34 0.006905 46102 33727 1.3719 909.298 35 34 0.007156 74842 53934 1.39 20 831.270 35 34 0.009120143725 91221 1.58 21 1385.601 31 30 0.009217 3924 10480 0.37 22 1435.73130 33 0.009711 8573 5446 1.57 23 1377.789 40 31 0.011505 6101 3161 1.9324 2378.220 40 33 0.014566 10901 5014 2.17 25 1210.582 28 34 0.01558180413 47905 1.68 26 1401.705 31 28 0.015734 6300 4004 1.57 27 960.475 4233 0.017667 27006 13464 2.01 28 850.438 28 33 0.018992 99230 46253 2.1529 1510.791 42 29 0.019051 5149 2726 1.89 30 1489.865 38 29 0.0191784522 2586 1.75 31 1364.628 34 31 0.023863 5368 3905 1.37 32 1023.640 5029 0.024563 10988 4121 2.67 33 954.542 25 30 0.025792 13945 7730 1.80 34829.268 37 28 0.026432 73762 46511 1.59 35 1129.473 35 33 0.026785 151289526 1.59 36 2092.117 35 28 0.028361 11369 5541 2.05 37 1078.087 20 280.029207 6275 4129 1.52 38 1141.652 35 32 0.029435 25135 19459 1.29 39892.429 36 32 0.034460 34071 21526 1.58 40 1112.553 33 29 0.037514 100495181 1.94 41 847.248 36 30 0.040127 52275 29856 1.75 42 1148.510 28 300.040211 5540 10433 0.53 43 1504.820 40 34 0.041511 30383 15588 1.95 44723.197 19 28 0.042047 5110 3221 1.59 45 2051.080 38 28 0.043654 28751920 1.50 46 918.550 25 32 0.045376 18757 12421 1.51 47 925.281 34 320.047311 18635 11566 1.61 48 1521.775 33 30 0.047430 6822 16717 0.41 491326.630 29 28 0.047724 3003 5721 0.52 50 1312.680 22 29 0.049059 40132748 1.46 51

Example 3 Identification of Peptide Amino Acid Sequences

Using the software programs Matrix Science Mascot and Protein PilotParagon, amino acid sequences were tentatively assigned to a total of 17peptides (Table 1) corresponding to six parent proteins. These peptidefragments were derived from a fibronectin III domain of Oncostatin Mreceptor beta chain (OSMRβ), fibrinogen alpha chain (FGA),fibrinogen/fibrinopeptide B (FGB), a fragment of the signal peptideregion of the cysteine and histidine-rich protein 1 (CYHR1), coagulationfactor XIII chain A (F13A) and Complement C3 (CO3). One peptide(1534.689 m/z) was assigned slightly different but overlapping aminoacid sequences by the Mascot and the Paragon algorithms. Seven peptidemasses required post-translational modifications to explain MS/MSfragmentation spectra. Four peptides were N-terminally modifiedincluding two FGA modifications that were assigned a mass value only.One FGA modification was assigned as a post-translationally hydroxylatedphenylalanine given that the F27Y polymorphism has not been reported.One FGB peptide was assigned with an N-terminal gyro-glutamate residueresulting from an N-terminal glutamine rearrangement. Two OSMR peptideswere assigned mass values consistent with modifications includingdi-sodiation (+45.99 m/z) and O-glucosamine (O-GlcN) modification

Example 4 Differential Expression of Intact OSMRIβ and CYHR1 in PatientSerum

Immunoblotting experiments were performed to determine if the intactOSMRIβ and CYHR1 proteins in serum correlated with the differentialpeptide expressions that were observed. In reducing and denaturingconditions, an OSMR positive band was identified migrating at 50 kDa(FIGS. 4D-E) and was significantly (p<0.05) increased (75% above poorresponders) in the serum of good responders. The analysis of thesesamples using non-reducing and denaturing SDS-PAGE gels identified OSMRbands migrating at 100-110 kDa with a like expression trend. Similarly,CHYR1 was identified (FIG. 5C) and validated using immunogen peptideblocking experiments (FIG. 5D) migrating at approximately 72 kDa and wassignificantly (FIG. 5B; p<0.05) increased in the serum of EPOhypo-responders (30% above good responders).

Example 5 Statistical Analysis of Identified Peptides

Summary statistics for all identified peptides are shown in Table 6. Inthe case of OSMRIβ and FGA, more than one fragment of a parent proteinwas identified and a Bonferroni adjusted p-value is shown and ananalysis of the sum of the fragment abundances was performed. Inaddition, the ROC value associated with the sensitivity and specificityof the peptide to predict either good or poor response was calculated.

TABLE 6 Statistical Analysis of the Identified Peptides. Gender (pPeptide m/z Group values+) Interaction ROC* OSMR 1273 <0.0001 (<0.0001)0.040 (1.00)  0.85 (1.00) 0.95 1549 <0.0001 (<0.0001) 0.026 (0.08)  0.21(0.63) 0.96 1664 <0.0001 (<0.0001) 0.19 (0.56) 0.62 (1.00) 0.99 Sum ofFragments <0.0001 0.20 0.65 0.98 CYHR1 1488 <0.0001 0.60 0.60 0.089 FGA1194 0.052 (0.47)  0.49 (1.00) 0.29 (1.00) 0.21 1399 0.081 (0.73)  0.67(1.00) 0.92 (1.00) 0.38 1463 0.021 (0.19)  0.58 (1.00) 0.33 (1.00) 0.311481 0.045 (0.041) 0.46 (1.00) 0.80 (1.00) 0.28 1534 0.063 (0.57)  0.78(1.00) 0.85 (1.00) 0.38 2466 0.03 (0.27) 0.067 (0.60)  0.85 (1.00) 0.182553 0.019 (0.17)  0.27 (1.00) 0.59 (1.00) 0.19 2768 0.053 (0.48)  0.16(1.00) 0.58 (1.00) 0.23 2931 0.004 (0.036) 0.17 (1.00) 0.33 (1.00) 0.19Sum of Fragments 0.005 0.17 0.59 0.12 FGB 1552 0.0010 0.89 0.72 0.20Factor XIII 1210 0.015 0.51 0.71 0.25 Complement C3 1504 0.07 0.64 0.200.26 *values for ROC are the area under the curve with values greaterthan 0.5 predictive of poor response and values less than 0.5 predictiveof good response +p values follow Bonferroni correction for multiplecomparisons

Discussion of Examples 1-5

One of the goals of the study was to identify serum peptides associatedspecifically with a poor response to EPO. To that end, patients thatroutinely attended their dialysis session, received adequate EPO andiron dosing, and did not appear to have risk factors for erythropoietinfailure, such as chronic inflammation or infection, were studied. Usinga peptidomic approach to generate MS data and develop a list ofdifferentially abundant peptides and ranked on p-values, amino acidsequences were assigned to 16 peptides whose serum abundancesignificantly differed between poor and good responders for furtheranalysis. Three of the serum peptides associated with poor EPO response,through sequence alignment of the peptides to the parent protein, werefound to be derived from the fibronectin III domain of the OSMRIβ chain.The 13 serum peptides associated with good EPO response were observed tobe derived from FGA, FGB, FXIIIA, CO3, and CYHR1.

Whether the serum peptide fragment differences reflected changes in theintact protein in the serum was also examined. To that end, animmunoblot analysis of the serum for the presence of OSMRIβ (reducingand non-reducing conditions) and CYHR1 (reducing conditions) wasperformed in a subset of the total population. The results of the OSMRβimmunoblot experiments suggested that the receptor is present in theserum as a dimer. The molecular weight of the receptor observed inreducing conditions was consistent with molecular weights for shed OSMR,LIF, and IL-6R ecto-domains (11, 12). The presence of both intactproteins in serum was also demonstrated, with OSMR increased in theserum of good responders and CYHR1 increased in the serum of poorresponders.

In comparing the abundance of intact protein by immunoblot to peptidefragments from LCMS, different patterns were observed. For OSMR, intactprotein was high in the serum of good responders while peptide fragmentswere high in poor responders. For CYHR1, intact protein was high in theserum of poor responders while peptide fragments were high in the serumof good responders. Without wishing to be bound by any particulartheory, it was thought that the difference was due to altered catabolismof OSMR and CYHR1 over the range of ERI or increased receptor turnoverin the case of OSMR. Animal data appear to support this speculation forOSMR, where OSMR knockout mice have low hematocrit and decreased RBC's(13).

These findings were not confounded with other measured markers of EPOresponse. Differences between poor and good responders were not observedfor C-reactive protein, hepcidin, IL-6, IL-7, IL-8, IL-10, TNF-α,transferrin saturation (Tsat), ferritin, and albumin. There was asignificant interaction between responder type and gender for hepcidin,IL-6 and IL-8. It was thought that the gender interaction is most likelyrelated to several male poor responders that showed signs ofinflammation in their measured laboratory values.

Three fragments of OSMRIβ were found to be strongly associated with apoor EPO response and one fragment of CYHR1 was found to be stronglyassociated with a good EPO response. Oncostatin-M (OSM) is proposed tobe an important EpoR-phosphoY343-Stat5 induced gene product thatparticipates in erythroblast survival (14). OSM is secreted fromcytokine activated T cells and monocytes and is involved in inflammation(15,16). OSM binds to two different OSM receptors in humans: the type 1receptor is identical to leukemia inhibitory factor (LIF) receptor thatconsists of gp130, also found in the IL-6 receptor; and, the type 2receptor which consists of gp130 and OSM-specific receptor 0 subunit(OSMR) (17,18). The OSMR fragments identified in the serum of thepresent patients were from the type 2 receptor.

Animal studies indicate that OSMR may play an important role inerythropoiesis as OSMR knockout mice have a decreased number ofcirculating RBC and a decreased hematocrit compared to wild type (13).OSMR knockout mice also have decreased numbers of erythroid colonyforming units and erythrocyte-producing colonies in the bone marrow.Work in human fibroblast or epithelial cells show that OSM ligandbinding to OSMR induces receptor degradation and then increases thelevel of receptor synthesis (19). In hepatocytes and hepatoma cells, OSMinduces hypoxia-inducible factor 1α gene transcription via a Januskinase/signal transducer (20).

Analysis of the estimated amino acid sequence of the fragment of CYHR1showed that the peptide was enriched in hydrophobic amino acids andderived from the signal peptide sequence of CYHR1. This enrichment ofhydrophobic amino acids was consistent with the peptide being recoveredfrom the serum interactome fraction (the protein bound serum peptidefraction). This CYHR1 fragment was a similar predictor of a goodresponse (ROC=0.91) as OSMR was observed to be a predictor of a poorresponse (ROC=0.98).

The current state of knowledge on CYHR1 is limited to its predictedprotein structure, protein-protein interactions, subcellularlocalization and chromosome mapping. CYHR1 is proposed to contain fourfunctional transmembrane helices and was first identified using a yeasttwo-hybrid system to search for cytoplasmic proteins that associate withgalectin-3 (21). Subcellular localization of CYHR1 in 3T3 cells byconfocal microscopy showed concentrations at the nuclear envelope andcytoplasm, but not in the nucleus. It was not clear from the publisheddata if the cytoplasmic pool is resident in a unique organellar membranefraction or truly cytoplasmic. Further work was performed usingrecombinant hamster galectin-3 and murine CYHR1 and demonstrated thatCYHR1 binds to the carbohydrate-recognition domain of galectin-3 (22).

Other peptides were also identified in the serum of these subjects thathad increased abundances in good responders. These peptides wereattributed to FGA, FGB, F XIIIA, and CO3 and may be related to lowlevels of inflammation that are present in hemodialysis patients (23).The prediction of EPO response has been related to the baselinefibrinogen, baseline transferrin receptor concentration and the changein the transferrin receptor concentration after 2 weeks for EPO therapy(3). The observed increase in abundance of fragments of both fibrinogenand factor XIII maybe related through thrombin and a result ofinflammation (24). In a study of 100 hemodialysis patients in which manyproposed markers of inflammation were measured, the authors concludedthat subclinical inflammation was an important determinant of anemia(25). Further, the authors of this manuscript were able to look at 51subjects that had not received EPO and found that there was a negativerelationship between Hb and fibrinogen in ESA treated subjects but notin non-ESA treated subjects.

In summary, a peptidomic analysis was performed on the serum of subjectswithout overt signs of inflammation or extraordinary blood loss thatwere good- and poor-responders to exogenous EPO. The analysis resultedin the identification of 16 peptide fragments that were differentiallyexpressed in the two groups, with OSMRβ and CYHR1 showing a goodassociation. The other identified fragments, fibrinogen α and β, factorXIII, and compliment C3, were not as strongly associated with ESAresponse and may reflect an underlying inflammatory process.

Throughout this document, various references are mentioned. All suchreferences are incorporated herein by reference, including thereferences set forth in the following list:

REFERENCES

-   1. Zhang, Y., Thamer, M., Stefanik, K., Kaufman, J.,    Cotter, D. J. 2004. Epoetin requirement predict mortality in    hemodialysis patients. Am. J. Kidney Dis. 44:866-876.-   2. Szczech. L. A., Barnhart, H. X., Inrig, J. K., Reddan, D. N.,    Sapp, S., Califf, R. M., Patel, U. D., Singh, A. K. 2008. Secondary    analysis of the CHOIR trial epoetin-α dose and achieved hemoglobin    outcomes. Kidney Int. 74:791-798.-   3. Danielson, B. 1995. R-HuEPO hyporesponsiveness—who and why?    Nephrol. Dial. Transplant. 10:69-73.-   4. Goicoechea, M., Martin, J., de Sequera, P., Quiroga, J. A. Ortiz,    A., Carre{hacek over (n)}o, V., Caramelo, C. 1998. Role of cytokines    in the response to erythropoietin in hemodialysis patients. Kidney    Int. 54:1337-1343.-   5. Van der Putten, K., Braam, B., Jie, K. E.,    Gaillard, C. A. J. M. 2008. Mechanisms of disease: erythropoietin    resistance in patients with both heart and kidney failure. Nat.    Clin. Pract. Nephrol. 4:47-57.-   6. Nemeth, E., Rivera, S., Gabayan, V., Keller, C., Taudorf, S.,    Pedersen, B. K., Ganz, T. 2004. IL-6 mediates hypoferremia of    inflammation by inducing the synthesis of the iron regulatory    hormone hepcidin. J. Clin. Invest. 113:1271-1276.-   7. Andrews, N.C. 2004. Anemia of inflammation: the cytokine-hepcidin    link. J. Clin. Invest. 113:1251-1253-   8. Khankin, E. V. Mutter, W. P., Tamez, H., Yuan, H. T.    Karumanchi, S. A., Thadhani, R. 2010. Soluble erythropoietin    receptor contributes to erythropoietin resistance in end-stage renal    disease. PLoS One. 16:e9246.-   9. Inrig, J. K., Patel, U., Bryskin, S., Szczech, L. 2009.    Association between high-dose ESA, inflammatory biomarkers, and    soluble erythropoietin receptors. J. Am. Soc. Nephrol. 20:143A.-   10. Mann, M. and Kelleher, N. L. 2008. Precision proteomics: The    case for high resolution and high mass accuracy. Proc. Nat. Acad.    Sci. 105:18132-18138-   11. Matthews V., Schuster B., Schütze S., Bussmeyer I., Ludwig A.,    Hundhausen C., Sadowski T., Saftig P., Hartmann D., Kallen K. J.,    Rose-John S. 2003. Cellular cholesterol depletion triggers shedding    of the human interleukin-6 receptor by ADAM10 and ADAM17 (TACE). J    Biol Chem. 278:38829-39-   12. Chen D, Chu C Y, Chen C Y, Yang H C, Chiang Y Y, Lin T Y, Chiang    I P, Chuang D Y, Yu C C, Chow K C. 2008 Expression of short-form    oncostatin M receptor as a decoy receptor in lung adenocarcinomas. J    Pathol. 215:290-9-   13. Tanka, M., Hirgayashi, Y., Sekiguchi, T., Inoue, T., Katsuki,    M., Miyajima, A. 2003. Targeted disruption of oncostatin M receptor    results in altered hematopoiesis. Blood. 102:3154-3162.-   14. Menon, M. P., Karur, V., Bogacheva, O., Cuetarea, B.,    Wojchowski, D. M. 2006. Signals for stress erythropoiesis are    integrated via and erythropoietin receptor-phosphotyrosine-343-Stat5    axis. J. Clin. Invest. 116:683-694.-   15. Brown, T. J., Lioubin, M. N., Marquardt, H. 1987. Purification    and characterization of cytostatic lymphokines produced by activated    human T lymphocytes: synergistic antoproliferative activity of    transforming growth factor beta 1, interferon-gamma, and oncostatin    M for human melanoma cells. J. Immunol. 139:2977-2983.-   16. Malik, N., Kallestad, J. C., Gunderson, N. L., Austin, S. D.,    Neubauer, M. G., Ochs, V., Marquardt, H., Zarling, J. M., Shoyab,    M., Wei, C. M., et al. 1989. Molecular cloning, sequence analysis,    and functional expression of a novel growth regulator, oncostatin M.    Mol. Cell Biol. 9:2847-2853.-   17. Thoma B, Bird T A, Friend D J, Gearing D P, Dower S K. 1994.    Oncostatin M and leukemia inhibitory factor trigger overlapping and    different signals through partially shared receptor complexes. J    Biol Chem. 269:6215-22.-   18. Mosley B, De Imus C, Friend D, Boiani N, Thoma B, Park L S,    Cosman D. 1996. Dual oncostatin M (OSM) receptors. Cloning and    characterization of an alternative signaling subunit conferring    OSM-specific receptor activation. J Biol Chem. 271:32635-32643.-   19. Blanchard, F., Wang, Y., Kinzie, E., Durlomb, L., Godard, A.,    Baumann, H. 2001. Oncostatin M regulates the synthesis and turnover    of gp130, leukemia inhibitory factor receptor α, and oncostatin M    receptor β by distinct mechanisms. J. Biol. Chem. 50:47038-47045.-   20. Vollner, S., Kappler V., Kaczor, J., Flügel, D., Rolvering, C.,    Kato, N., Kietzman, T., Behrmann, I., Haan, C. 2009.    Hypoxia-inducible factor 1α is up-regulated by oncostatin M and    participates in oncostatin M signaling. Hepatology 50:253-260.-   21. Menon, R. P., Strom, M., Hughes, R. C. 2000. Interaction of a    novel cysteine and histidine-rich cytoplasmic protein with    galectin-3 in a carbohydrate-independent manner. FEBS Lett.    470:227-231.-   22. Bawumia, S. Barboni, E. A. M., Menon, R. P., Hughes, R. C. 2003.    Specificity of interactions of galectin-3 with Chrp a cysteine- and    histidine-rich cytoplasmic protein. Biochimie 85:189-194.-   23. Kaysen G. A. 2001. The microinflammatory state in uremia: causes    and potential consequences. J. AM. Soc. Nephrol. 12:1549-1557.-   24. Narayanan, S. 1999. Multifunctional roles of thrombin. Ann.    Clin. Lab. Sci. 29:275-280.-   25. Borawski, J., Pawlak, K., Myśliwiec, M. 2002. Inflammatory    markers and platelet aggregation tests as predictors of hemoglobin    and endogenous erythropoietin levels in hemodialysis patients.    Nephron. 91:671-681.-   26. Merchant, M. L., Perkins, B. A., Boratyn, G. M., Ficociello, L.    H., Wilkey, D. W., Barati, M. T., Bertram, C. C., Page, G. P.,    Rovin, B. H., Warram, J. H., et al. 2009. Urinary peptidome may    predict renal function decline in type 1 diabetes and    microalbuminuria. J Am Soc Nephrol 20:2065-2074.-   27. Merchant, M. L., Cummins, T. D., Wilkey, D. W., Salyer, S. A.,    et al., 2008. Proteomic analysis of renal calculi indicates an    important role for inflammatory processes in calcium stone    formation. Am J Physiol Renal Physiol 295, F1254-1258.

It will be understood that various details of the presently disclosedsubject matter can be changed without departing from the scope of thesubject matter disclosed herein. Furthermore, the foregoing descriptionis for the purpose of illustration only, and not for the purpose oflimitation.

What is claimed is:
 1. A method for predicting a response to an erythropoietic agent in a subject, comprising: (a) providing a biological sample from the subject; (b) determining an amount in the sample of at least one peptide selected from the group consisting of SEQ ID NOS: 1-12 and 14-17; (c) comparing the amount of the at least one peptide in the sample, if present, to a control level of the at least one peptide; (d) predicting that the subject will have a good response to the erythropoietic agent if there is a measurable difference in the amount of the at least one peptide selected from the group consisting of SEQ ID NOS: 1-12 and 14 in the sample as compared to the control level; and (e) predicting that the subject will have a poor response to the erythropoietic agent if there is a measurable difference in the amount of the at least one peptide selected from the group consisting of SEQ ID NOS: 15-17 in the sample as compared to the control level.
 2. The method of claim 1, further comprising applying the biological sample to a device capable of affecting detection of the at least one peptide.
 3. The method of claim 1, wherein the subject has kidney disease, anemia, or cancer.
 4. The method of claim 1, wherein the biological sample comprises blood, plasma, serum, or urine.
 5. The method of claim 1, wherein the subject is human.
 6. The method of claim 1, wherein determining the amount in the sample of the at least one peptide comprises determining the amount in the sample of the at least one peptide using mass spectrometry (MS) analysis, immunoassay analysis, or both.
 7. The method of claim 6, wherein the immunoassay analysis comprises an enzyme-linked immunosorbent assay (ELISA).
 8. The method of claim 1, further comprising selecting an amount or modifying an amount of the erythropoietic agent to be administered to the subject based on the determined amount of the at least one peptide.
 9. The method of claim 1, further comprising, prior to (a), selecting a subject for treatment with an erythropoietic agent.
 10. The method of claim 1, further comprising administering the erythropoietic agent to the subject based on the result of the predicting step (d) or the result of the predicting step (e).
 11. The method of claim 10, wherein administering the erythropoietic agent to the subject comprises administering a differing amount of the erythropoietic agent to a subject based on whether the subject is predicted to have a good response to the erythropoietic agent or is predicted to have a poor response to the erythropoietic agent.
 12. A method for determining whether to modify an amount of an erythropoietic agent administered to a subject, comprising: (a) providing a series of biological samples over a time period from the subject; and (b) analyzing the series of biological samples to determine an amount in each of the biological samples of at least one peptide selected from the group consisting of SEQ ID NOS: 1-12 and 14-17. (c) comparing any measurable change in the amounts of the at least one peptide in each of the biological samples over the time period; (d) identifying the subject as being in need of an administration of a decreased amount of the erythropoietic agent if there is a measurable difference in the amount of the at least one peptide selected from SEQ ID NOS: 1-12 and 14 over the time period; and (e) identifying the subject as being in need of an administration of an increased amount of the erythropoietic agent if there is a measurable difference in the amount of the at least one peptide selected from SEQ ID NOS: 15-17 over the time period.
 13. The method of claim 12, further comprising the step of administering a decreased amount of the erythropoietic agent to the subject if there is a measurable difference in the amount of the at least one peptide selected from SEQ ID NOS: 1-12 and 14 over the time period.
 14. The method of claim 12, further comprising the step of administering an increased amount of the erythropoietic agent to the subject if there is a measurable difference in the amount of the at least one peptide selected from SEQ ID NOS: 15-17 over the time period.
 15. The method of claim 12, wherein the subject has kidney disease, anemia, or cancer.
 16. The method of claim 12, wherein the biological sample comprises blood, plasma, serum, or urine.
 17. The method of claim 12, wherein the subject is human.
 18. The method of claim 12, wherein the series of biological samples comprises a first biological sample collected prior to modifying the amount of the erythropoietic agent administered to the subject and a second biological sample collected after modifying the amount of the erythropoietic agent administered to the subject.
 19. The method of claim 14, wherein determining the amount in the sample of the at least one peptide comprises determining the amount in the sample of the at least one peptide using mass spectrometry (MS) analysis, immunoassay analysis, or both.
 20. The method of claim 19, wherein the immunoassay analysis comprises an enzyme-linked immunosorbent assay (ELISA). 